Performance Characterization Model For A Cloud Control Plane

The control plane of a cloud infrastructure is responsible for managing and orchestrating the cloud resources, including provisioning, metering, monitoring, and security. Cloud user experience largely depends on the performance, availability and reliability of the control plane hardware and software stack managed by a cloud controller. Given that cloud is a large-scale multi-tenant environment, the load on cloud controller can increase dramatically with thousands of requests. The performance of the control plane is measured mainly by the time behavior and resource utilization and is affected by several factors such as the scale of the environment, load on cloud controller and resource constraints. Huge delays or time-out failures in serving the requests can become a common scenario in a highly scaled environment leading to bad user experience. Distributed tracing and root causing of such performance incidents, characterizing across the multi-layered control plane stack is a complex activity that needs a systematic approach and usage of cohesive tools for diagnosis as well as proactive resolution. To address these requirements, we discuss a Performance Characterization Model (PCM) in this paper, as a workflow for fine grained data driven evaluation to detect optimization areas and resolve performance problems. This model lays out a systematic approach through different phases of use-case analysis, load generation, metric characterization, data collection, analysis, and insight generation, as well as predicting performance thresholds based on data. We also demonstrate a specific case study for characterizing the performance of user interface of Cloud using the methodologies and tools of PCM.